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If Mark Kimura succeeds, the arduous — and at times dangerous — legwork needed to assess damaged utility lines after a disaster soon will be a thing of the past.
Instead of people, drones will survey the damage. More important, Kimura is training a computer to make sense of the drone footage and evaluate the problems, to tell the difference between, say, a fallen power pole and a fallen tree.
It’s a deceptively complex task, given the myriad types of utility poles and many ways a pole can be damaged, says Kimura, a senior data scientist with the Honolulu research and development firm Oceanit.
The human brain can understand such things easily, intuitively; even if people have never encountered a particular type of utility pole, they usually can infer the object is a utility pole by drawing on the complex data stored in the brain, Kimura says. The same goes with knowing whether a pole is damaged.
“Now, the computers are able to do this stuff,” says Kimura, whose work is being funded by a grant from the U.S. Department of Energy.
The problem for organizations in Hawaii is finding people like Kimura who can build the systems needed to do such analyses.
Entities ranging from university departments and government institutions to large corporations are hiring data scientists like Kimura: people who can create programs to make useful sense of the increasingly vast amounts of data that are easily available and cheap to store. Hawaii’s universities see training these workers as a way to strengthen the economy; it could mean a significant number of high-paying jobs for local people.
“Data is the new oil, or the black gold,” says Jason Leigh, co-director of the University of Hawaii’s Data Science Institute. “If you can just mine it, you can understand what customers want.”
Firms are “swimming or drowning in data,” says Helen Turner, vice president of innovation and dean of the Division of Natural Sciences and Mathematics at Chaminade University. And that means opportunities for a new type of worker.
“Nationally, you’re talking about millions of jobs,” she said.
Both Chaminade and UH have initiatives to train workers for data occupations. UH’s Data Science Institute is serving as a hub for collaboration among departments and organizations outside the system, which gives students significant experience in data science. This includes projects with partners like the Hawaii State Energy Office and the National Security Agency to use visualizations, including 3D models, to make sense of complex data.
Turner, meanwhile, is leading Chaminade’s effort to create a bachelor’s degree in data science to train workers for everything from smaller nonprofits to big companies like banks and utilities.
“We’re hoping our students can be the data whisperers for these sorts of institutions,” said Turner.
Exactly how many data scientists are employed in Hawaii is not clear, in part because the U.S. Bureau of Labor Statistics has no job classification for the occupation, Turner said.
Meanwhile, she said, there’s not even a standard term for the workers: some companies might call them data scientists, others data analysts.
One thing that is known is there are plenty of job openings. A search using the term “data scientist” on the job site Indeed.com turns up dozens of openings in Hawaii, at organizations like Hawaiian Airlines, First Hawaiian Bank, Central Pacific Bank and the consulting firm Booz Allen Hamilton, as well as government organizations. Salaries range from $57,000 on the low end to more than $115,000 on the high end.
“There’s a great interest in it,” said corporate recruiter Mary Despe, owner of MK Despe Consulting, who has worked to place data scientists with big firms in finance and healthcare. Especially attractive to employers are data scientists who “have actually done it as paid work for organizations.”
So why the sudden, exploding interest in data scientists, and what exactly do they do anyway?
A major factor is the ability to amass enormous amounts of data and store it relatively cheaply, said Gwen Jacobs, a neuroscientist who is co-director of UH’s Data Science Institute. The availability of data has surged so quickly, she said, that even big universities with degree programs, like the University of California, Berkeley, can’t keep up with demand for data scientists.
“They may not call it a data scientist, but is requires the same set of skills,” said Jacobs, who is also UH’s director of cyberinfrastructure.
To understand what data scientists do, it’s instructive to look at one of UH’s recent hires and what he’s doing.
Peter Sadowksi has a doctorate in computer science from the University of California, Irvine, and has published papers in journals focused on artificial intelligence and neural networks, which are computer systems modeled on the human brain and nervous system.
Sadowski’s work at UH cuts across a variety of disciplines. One project involves using artificial intelligence to study satellite images of the oceans to understand the movements of waves and sea life. He’s collaborating with atmospheric scientists to use machine learning to better understand how clouds form and operate.
And working with UH physicists, he’s using artificial neural networks to try to understand what happens when subatomic particles collide while traveling at nearly the speed of light, mind-bending experiments investigating the origins of matter at a massive particle accelerator in Japan.
What all of the work has in common is it requires something that can make sense of vast amounts of data, much the way the human brain can make sense of the enormous amounts of stimuli it constantly receives from the five senses.
“Data is the new oil, or the black gold.” — Jason Leigh, co-director of the University of Hawaii’s Data Science Institute.
“That analogy runs quite deep,” Sadowski said.
Concerning the particle experiments, for instance, he said, “Quite literally you’re training a neural network to see the particles.”
Collaborations are key. A case in point is UH’s Laboratory for Advanced Visualization and Applications. The lab takes up half of the ground floor of a building on the Manoa campus and has a decidedly skunkworks atmosphere, with a life-sized model of R2D2 trash bin, a spaniel named Clyde and a “virtual reality cave” where visitors can hover in orbit above the International Space Station or explore undersea ocean wrecks.
One project on display is a 3D model of Oahu, forecasting what the state’s power supplies will look like in 2045, by which time the state is supposed to be producing all of its electricity from renewable resources, like wind and solar.
Meanwhile, in another office, doctoral student Alberto Gonzalez was working on a program used to visually map the frequency that clusters of related words and terms appear in a vast catalog of academic journals. Although the work might seem academic, the National Security Agency is funding the research because it sees the program as useful for analyzing content from social media posts to spot security threats, Gonzalez said.
The NSA did not respond to an emailed request for comment.
For businesses, the applications are seemingly endless. The darker side involves people like the billionaire hedge-fund investor Robert Mercer, who used algorithmic trading to make a fortune in the stock market then went on to fund Cambridge Analytica, the British consulting outfit that used data from Facebook to help President Donald Trump get elected.
The need for data analysis in the sciences means many scientists can work as data analysts, even if they didn’t train as computer scientists.
Despe recalls recruiting one scientist for a corporate job as a data scientist even though the scientist had no formal training in the field. The scientist had spent years analyzing data as part of his research, however, and had volunteered his free time analyzing public health data to track movements of the Ebola virus.
“He was just kind of floored when I contacted him for a business-related job,” she recalls.
Not all data jobs require such high-level expertise, says Turner, the Chaminade data science program head. In some instances, it might be enough to be able to do high level spreadsheet work, knowing the best ways to use charts and graphs to tell an organization’s story.
Chaminade’s plan is to train an array of workers: from full-fledged degree holders to people only seeking a data science minor or certificate. Chaminade now has a faculty of two data scientists and plans to expand to four. UH’s Data Science Institute has five directors, faculty and researchers.
Like so many other data scientists, Oceanit’s Kimura gained his skills earning a doctorate in regional science, which involves disciplines like demographics and analysis of geographical data. Kimura has recently volunteered his expertise studying the impacts of lava from Kilauea Volcano on the Big Island’s Puna District.
Kimura’s colleague at Oceanit, Ian Kitajima, sees applying the artificial intelligence system Kimura is developing to all sorts of tasks needed to run a city, to spot potholes for instance, or find places where graffiti is starting to pop up.
And for Kimura, the work is uniquely fulfilling.
“If there was no Oceanit, I probably wouldn’t be here,” he says.
“Hawaii’s Changing Economy” is supported by a grant from the Hawaii Community Foundation as part of its CHANGE Framework project.
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